ModelsWhen the robot model becomes an API, the next demonstration becomes the scarce asset
Physical Intelligence’s beta shifts attention from obtaining a model to knowing exactly what to teach it next.
Model releases and architectures: what changes in capability, efficiency and control.
LLMs · VLMs · VLAs · World models · Image, video & audio · Embeddings

12 articles
ModelsPhysical Intelligence’s beta shifts attention from obtaining a model to knowing exactly what to teach it next.
ModelsAUGUstus puts reasoning supervision into training while allowing action-only inference. That also changes what an explanation can prove.
ModelsTapNav plans contact with the surroundings because a slightly longer walk can produce a better estimate of position.
ModelsAn OpenWAM experiment suggests that stripping context from a motor component can make it easier to reuse.
ModelsAnthropic brings adjustable reasoning to its small-model tier. The savings depend on what survives the handoff to a larger model, not just the price of the first answer.
ModelsThe multimodal preview highlights a costly blind spot in document AI: a plausible answer may come from the wrong chart, label or footnote. Test what the model saw before scoring what it concluded.
ModelsReflection trains its model to avoid unnecessary reasoning tokens. The business test is whether it removes wasted work without increasing failed attempts or human correction.
ModelsGoogle’s compact model searches across text, images, video and audio in a shared representation. Its useful advantage may be a simpler retrieval pipeline, provided it finds the records that actually matter.
ModelsDeepSeek separates the work of reading from answering and reports a smaller context cache. For long-running systems, the opportunity is to retain useful evidence at a lower cost—not simply generate tokens faster.
ModelsOpenAI positions Sol near its pricier Astra on selected evaluations. The practical opportunity is moving routine work to a cheaper model while identifying the exceptions that still need more capability.
ModelsGoogle DeepMind’s transfer claims point to a potentially scalable model business: reuse learned skills across different bodies. The test is total adaptation effort, including data collection and validation.
ModelsThe steerable model explores whether richer instructions can reuse skills already learned. The business opportunity is fewer new demonstrations; the unresolved cost is the human guidance needed to make it work.
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